The image of the Aekley function. حسب Zhengyu Xu (8550660)

The pseudocode for the NAFPSO algorithm. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

PSO algorithm flowchart. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

The benchmark functions. حسب Shuhui Yu (1535500)

Scheduling time of five algorithms. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

Convergence speed of five algorithms. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional حسب Ryan Stocks (16867476)

"…We show that batched formation of the XC matrix from the density matrix yields the best performance for large (>O(103) basis functions), sparse systems such as glycine chains and water clusters. …"

Completion times for different algorithms. حسب Jianbin Zheng (587000)

"…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"

The average cumulative reward of algorithms. حسب Jianbin Zheng (587000)

"…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"

Simulation settings of rMAPPO algorithm. حسب Jianbin Zheng (587000)

"…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"

Knowledge graph model rating function. حسب Chunjuan Li (7890182)

Network structure diagram of LMD-YOLO algorithm. حسب Weiyu Han (3448742)

الموضوعات:

Network structure diagram of YOLOv8 algorithm. حسب Weiyu Han (3448742)

الموضوعات:

Loss Function Comparison. حسب Hongwei Yue (574068)

Loss Function Comparison. حسب Hongwei Yue (574068)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. حسب Yuanchen Zhao (12905580)

"…Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …"

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms حسب Saadiallakh Normatov (20682324)

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms حسب Saadiallakh Normatov (20682324)

Siou loss function calculation diagram. حسب Weiyu Han (3448742)

الموضوعات:

Acc epoch loss curve of IPCA algorithm. حسب Lu Lin (201289)